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import pandas as pd
import plotly.graph_objs as go
import plotly.express as px

df: pd.DataFrame = pd.read_csv('../datasets/emissions.csv')
df.head()
Area Item Element Unit 2000 2001 2002 2003 2004 2005 ... 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
0 Afghanistan Crop Residues Direct emissions (N2O) kilotonnes 0.520 0.5267 0.8200 0.9988 0.8225 1.1821 ... 1.0321 1.3726 1.4018 1.4584 1.2424 1.1940 1.0617 0.8988 1.2176 1.3170
1 Afghanistan Crop Residues Indirect emissions (N2O) kilotonnes 0.117 0.1185 0.1845 0.2247 0.1851 0.2660 ... 0.2322 0.3088 0.3154 0.3281 0.2795 0.2687 0.2389 0.2022 0.2740 0.2963
2 Afghanistan Crop Residues Emissions (N2O) kilotonnes 0.637 0.6452 1.0045 1.2235 1.0075 1.4481 ... 1.2643 1.6815 1.7173 1.7865 1.5220 1.4627 1.3005 1.1011 1.4916 1.6133
3 Afghanistan Crop Residues Emissions (CO2eq) from N2O (AR5) kilotonnes 168.807 170.9884 266.1975 324.2195 266.9995 383.7498 ... 335.0379 445.5958 455.0727 473.4174 403.3181 387.6130 344.6447 291.7838 395.2689 427.5284
4 Afghanistan Crop Residues Emissions (CO2eq) (AR5) kilotonnes 168.807 170.9884 266.1975 324.2195 266.9995 383.7498 ... 335.0379 445.5958 455.0727 473.4174 403.3181 387.6130 344.6447 291.7838 395.2689 427.5284

5 rows × 25 columns

elem = df['Element'].value_counts()
elem

Element
Emissions (CO2eq) (AR5)                 11926
Emissions (N2O)                          9622
Emissions (CO2eq) from N2O (AR5)         9486
Emissions (CH4)                          8310
Emissions (CO2eq) from CH4 (AR5)         8167
Emissions (CO2)                          6677
Direct emissions (N2O)                   1912
Indirect emissions (N2O)                 1756
Emissions (CO2eq) from F-gases (AR5)      909
Name: count, dtype: int64

px.bar(df.where(df['Element'] == 'Emissions (CO2)'), x='Area', y='2000')

px.bar(df.where(df['Element'] == 'Emissions (CO2)'), x='Area', y='2001')
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